Analyzing social networks with D-miner Cloud

The Online Social Network (OSN) sites have been getting more and more popular in recent years and there are interests of having a tool to automatically retrieve and analyze the information in order to understand their related social behavior. This paper presents a framework of D-miner Cloud (DMC) based on a cloud architecture which can provide collection of the information from heterogeneous OSN sites, managing and analyzing the collected information afterwards. It has 5 components consisting of frontend devices, service gateway, service unit, central repository and OSN sites. We present the approach to implement the framework, integrate DMC and the Application Program Interfaces (API) of OSN sites, organize the communications in DMC framework and implement the mobile frontend design.

[1]  Christopher C. Yang,et al.  Generalizing terrorist social networks with K-nearest neighbor and edge betweeness for social network integration and privacy preservation , 2010, 2010 IEEE International Conference on Intelligence and Security Informatics.

[2]  Songqing Chen,et al.  Analyzing patterns of user content generation in online social networks , 2009, KDD.

[3]  Eugene Agichtein,et al.  On the evolution of the yahoo! answers QA community , 2008, SIGIR '08.

[4]  Chunming Rong,et al.  Social Impact of Privacy in Cloud Computing , 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

[5]  Aristides Gionis,et al.  Social Network Analysis and Mining for Business Applications , 2011, TIST.

[6]  Randy H. Katz,et al.  Above the Clouds: A Berkeley View of Cloud Computing , 2009 .

[7]  Jeffrey V. Nickerson,et al.  Developing web services choreography standards - the case of REST vs. SOAP , 2005, Decis. Support Syst..

[8]  Marco Gonzalez,et al.  Tastes, ties, and time: A new social network dataset using Facebook.com , 2008, Soc. Networks.

[9]  Li Fan,et al.  Developing a Dark Web collection and infrastructure for computational and social sciences , 2010, 2010 IEEE International Conference on Intelligence and Security Informatics.

[10]  Salvatore Catanese,et al.  Crawling Facebook for social network analysis purposes , 2011, WIMS '11.

[11]  Alessandro Acquisti,et al.  Information revelation and privacy in online social networks , 2005, WPES '05.

[12]  Johan Bollen,et al.  Twitter mood predicts the stock market , 2010, J. Comput. Sci..

[13]  Ramanathan V. Guha,et al.  The predictive power of online chatter , 2005, KDD '05.

[14]  R. Ackland Social Network Services as Data Sources and Platforms for e-Researching Social Networks , 2009 .

[15]  Vincent T. Y. Ng,et al.  Discovering potential drug abuse with fuzzy sets , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[16]  Soumya Banerjee,et al.  Mining Social Networks for Viral Marketing Using Fuzzy Logic , 2010, 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation.

[17]  Gilad Mishne,et al.  Capturing Global Mood Levels using Blog Posts , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[18]  Bernardo A. Huberman,et al.  Predicting the Future with Social Media , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[19]  Yiming Yang,et al.  Mining social networks for personalized email prioritization , 2009, KDD.

[20]  Theodoros Lappas,et al.  Finding a team of experts in social networks , 2009, KDD.

[21]  Melanie Haspels,et al.  Will you be my Facebook friend , 2008 .

[22]  Roy T. Fielding,et al.  Principled design of the modern Web architecture , 2000, Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium.